627 research outputs found

    Combining visible and infrared radiometry and lidar data to test simulations in clear and ice cloud conditions

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    Measurements taken during the 2003 Pacific THORPEX Observing System Test (P-TOST) by the MODIS Airborne Simulator (MAS), the Scanning High-resolution Interferometer Sounder (S-HIS) and the Cloud Physics Lidar (CPL) are compared to simulations performed with a line-by-line and multiple scattering modeling methodology (LBLMS). Formerly used for infrared hyper-spectral data analysis, LBLMS has been extended to the visible and near infrared with the inclusion of surface bi-directional reflectance properties. A number of scenes are evaluated: two clear scenes, one with nadir geometry and one cross-track encompassing sun glint, and three cloudy scenes, all with nadir geometry. <br><br> CPL data is used to estimate the particulate optical depth at 532 nm for the clear and cloudy scenes and cloud upper and lower boundaries. Cloud optical depth is retrieved from S-HIS infrared window radiances, and it agrees with CPL values, to within natural variability. MAS data are simulated convolving high resolution radiances. The paper discusses the results of the comparisons for the clear and cloudy cases. LBLMS clear simulations agree with MAS data to within 20% in the shortwave (SW) and near infrared (NIR) spectrum and within 2 K in the infrared (IR) range. It is shown that cloudy sky simulations using cloud parameters retrieved from IR radiances systematically underestimate the measured radiance in the SW and NIR by nearly 50%, although the IR retrieved optical thickness agree with same measured by CPL. <br><br> MODIS radiances measured from Terra are also compared to LBLMS simulations in cloudy conditions, using retrieved cloud optical depth and effective radius from MODIS, to understand the origin for the observed discrepancies. It is shown that the simulations agree, to within natural variability, with measurements in selected MODIS SW bands. <br><br> The impact of the assumed particles size distribution and vertical profile of ice content on results is evaluated. Sensitivity is much smaller than differences between measured and simulated radiances in the SW and NIR. <br><br> The paper dwells on a possible explanation of these contradictory results, involving the phase function of ice particles in the shortwave

    statistics of vertical backscatter profiles of cirrus clouds

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    Abstract. A nearly global statistical analysis of vertical backscatter and extinction profiles of cirrus clouds collected by the CALIOP lidar, on-board of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation, is presented. Statistics on frequency of occurrence and distribution of bulk properties of cirrus clouds in general and, for the first time, of horizontally homogeneous (on a 5-km field of view) cirrus clouds only are provided. Annual and seasonal backscatter profiles (BSP) are computed for the horizontally homogeneous cirri. Differences found in the day/night cases and for midlatitudes and tropics are studied in terms of the mean physical parameters of the clouds from which they are derived. The relationship between cloud physical parameters (optical depth, geometrical thickness and temperature) and the shape of the BSP is investigated. It is found that cloud geometrical thickness is the main parameter affecting the shape of the mean CALIOP BSP. Specifically, cirrus clouds with small geometrical thicknesses show a maximum in mean BSP curve located near cloud top. As the cloud geometrical thickness increases the BSP maximum shifts towards cloud base. Cloud optical depth and temperature have smaller effects on the shape of the CALIOP BSPs. In general a slight increase in the BSP maximum is observed as cloud temperature and optical depth increase. In order to fit mean BSPs, as functions of geometrical thickness and position within the cloud layer, polynomial functions are provided. The impact on satellite radiative transfer simulations in the infrared spectrum when using either a constant ice-content (IWC) along the cloud vertical dimension or an IWC profile derived from the BSP fitting functions is evaluated. It is, in fact, demonstrated that, under realistic hypotheses, the mean BSP is linearly proportional to the IWC profile

    Today is already Yesterday:\ua0The\ua0Glossa XX1 architectural project for the Italian Memorial in Block 21 at Auschwitz

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    The architect of the proposed Glossa XX Architectural Project for the Italian Memorial in Block " at Auschwitz, presents and elucidates the restorations it involves and its response to criticisms made by the Direction of the Auschwitz Museum

    Perception of Nigerian DĂčndĂșn talking drum performances as speech-like vs. music-like: The role of familiarity and acoustic cues

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    It seems trivial to identify sound sequences as music or speech, particularly when the sequences come from different sound sources, such as an orchestra and a human voice. Can we also easily distinguish these categories when the sequence comes from the same sound source? On the basis of which acoustic features? We investigated these questions by examining listeners’ classification of sound sequences performed by an instrument intertwining both speech and music: the dĂčndĂșn talking drum. The dĂčndĂșn is commonly used in south-west Nigeria as a musical instrument but is also perfectly fit for linguistic usage in what has been described as speech surrogates in Africa. One hundred seven participants from diverse geographical locations (15 different mother tongues represented) took part in an online experiment. Fifty-one participants reported being familiar with the dĂčndĂșn talking drum, 55% of those being speakers of YorĂčbĂĄ. During the experiment, participants listened to 30 dĂčndĂșn samples of about 7s long, performed either as music or YorĂčbĂĄ speech surrogate (n = 15 each) by a professional musician, and were asked to classify each sample as music or speech-like. The classification task revealed the ability of the listeners to identify the samples as intended by the performer, particularly when they were familiar with the dĂčndĂșn, though even unfamiliar participants performed above chance. A logistic regression predicting participants’ classification of the samples from several acoustic features confirmed the perceptual relevance of intensity, pitch, timbre, and timing measures and their interaction with listener familiarity. In all, this study provides empirical evidence supporting the discriminating role of acoustic features and the modulatory role of familiarity in teasing apart speech and music

    The DĂčndĂșn Drum helps us understand how we process speech and music

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    Every day, you hear many sounds in your environment, like speech, music, animal calls, or passing cars. How do you tease apart these unique categories of sounds? We aimed to understand more about how people distinguish speech and music by using an instrument that can both “speak” and play music: the dĂčndĂșn talking drum. We were interested in whether people could tell if the sound produced by the drum was speech or music. People who were familiar with the dĂčndĂșn were good at the task, but so were those who had never heard the dĂčndĂșn, suggesting that there are general characteristics of sound that define speech and music categories. We observed that music is faster, more regular, and more variable in volume than “speech.” This research helps us understand the interesting instrument that is dĂčndĂșn and provides insights about how humans distinguish two important types of sound: speech and music

    UV Raman lidar measurements of relative humidity for the characterization of cirrus cloud microphysical properties

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    Abstract. Raman lidar measurements performed in Potenza by the Raman lidar system BASIL in the presence of cirrus clouds are discussed. Measurements were performed on 6 September 2004 in the frame of the Italian phase of the EAQUATE Experiment. The major feature of BASIL is represented by its capability to perform high-resolution and accurate measurements of atmospheric temperature and water vapour, and consequently relative humidity, both in daytime and night-time, based on the application of the rotational and vibrational Raman lidar techniques in the UV. BASIL is also capable to provide measurements of the particle backscatter and extinction coefficient, and consequently lidar ratio (at the time of these measurements, only at one wavelength), which are fundamental to infer geometrical and microphysical properties of clouds. A case study is discussed in order to assess the capability of Raman lidars to measure humidity in presence of cirrus clouds, both below and inside the cloud. While air inside the cloud layers is observed to be always under-saturated with respect to water, both ice super-saturation and under-saturation conditions are found inside these clouds. Upper tropospheric moistening is observed below the lower cloud layer. The synergic use of the data derived from the ground based Raman Lidar and of spectral radiances measured by the NAST-I Airborne Spectrometer allows the determination of the temporal evolution of the atmospheric cooling/heating rates due to the presence of the cirrus cloud. Lidar measurements beneath the cirrus cloud layer have been interpreted using a 1-D cirrus cloud model with explicit microphysics. The 1-D simulations indicate that sedimentation-moistening has contributed significantly to the moist anomaly, but other mechanisms are also contributing. This result supports the hypothesis that the observed mid-tropospheric humidification is a real feature which is strongly influenced by the sublimation of precipitating ice crystals. Results illustrated in this study demonstrate that Raman lidars, like the one used in this study, can resolve the spatial and temporal scales required for the study of cirrus cloud microphysical processes and appear sensitive enough to reveal and quantify upper tropospheric humidification associated with cirrus cloud sublimation

    Phase shifts of synchronized oscillators and the systolic/diastolic blood pressure relation

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    We study the phase-synchronization properties of systolic and diastolic arterial pressure in healthy subjects. We find that delays in the oscillatory components of the time series depend on the frequency bands that are considered, in particular we find a change of sign in the phase shift going from the Very Low Frequency band to the High Frequency band. This behavior should reflect a collective behavior of a system of nonlinear interacting elementary oscillators. We prove that some models describing such systems, e.g. the Winfree and the Kuramoto models offer a clue to this phenomenon. For these theoretical models there is a linear relationship between phase shifts and the difference of natural frequencies of oscillators and a change of sign in the phase shift naturally emerges.Comment: 8 figures, 9 page

    Ice and mixed-phase cloud statistics on the Antarctic Plateau

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    Statistics on the occurrence of clear skies, ice clouds, and mixed-phase clouds over Concordia Station, in the Antarctic Plateau, are provided for multiple timescales and analyzed in relation to simultaneous meteorological parameters measured at the surface. Results are obtained by applying a machine learning cloud identification and classification (CIC) code to 4 years of measurements between 2012-2015 of downwelling high-spectral-resolution radiances, measured by the Radiation Explorer in the Far Infrared-Prototype for Applications and Development (REFIR-PAD) spectroradiometer. The CIC algorithm is optimized for Antarctic sky conditions and results in a total hit rate of almost 0.98, where 1.0 is a perfect score, for the identification of the clear-sky, ice cloud, and mixed-phase cloud classes. Scene truth is provided by lidar measurements that are concurrent with REFIR-PAD. The CIC approach demonstrates the key role of far-infrared spectral measurements for clear-cloud discrimination and for cloud phase classification. Mean annual occurrences are 72.3%, 24.9%, and 2.7% for clear sky, ice clouds, and mixed-phase clouds, respectively, with an inter-annual variability of a few percent. The seasonal occurrence of clear sky shows a minimum in winter (66.8%) and maxima (75%-76%) during intermediate seasons. In winter the mean surface temperature is about 9 C colder in clear conditions than when ice clouds are present. Mixed-phase clouds are observed only in the warm season; in summer they amount to more than one-third of total observed clouds. Their occurrence is correlated with warmer surface temperatures. In the austral summer, the mean surface air temperature is about 5gC warmer when clouds are present than in clear-sky conditions. This difference is larger during the night than in daylight hours, likely due to increased solar warming. Monthly mean results are compared to cloud occurrence and fraction derived from gridded (Level 3) satellite products from both passive and active sensors. The differences observed among the considered products and the CIC results are analyzed in terms of footprint sizes and sensors' sensitivities to cloud optical and geometrical features. The comparison highlights the ability of the CIC-REFIR-PAD synergy to identify multiple cloud conditions and study their variability at different timescales

    Emissivity retrievals with FORUM's end-to-end simulator: challenges and recommendations

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    Spectral emissivity is a key property of the Earth's surface, of which only very few measurements exist so far in the far-infrared (FIR) spectral region, even though recent work has shown that the FIR is important for accurate modelling of the global climate. The European Space Agency's 9th Earth Explorer, FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) will provide the first global spectrally resolved measurements of the Earth's top-of-the-atmosphere (TOA) spectrum in the FIR. In clear-sky conditions with low water vapour content, these measurements will provide a unique opportunity to retrieve spectrally resolved FIR surface emissivity. In preparation for the FORUM mission with an expected launch in 2027, this study takes the first steps towards the development of an operational emissivity retrieval for FORUM by investigating the sensitivity of the emissivity product of a full spectrum optimal estimation retrieval method to different physical and operational parameters. The tool used for the sensitivity tests is the FORUM mission's end-to-end simulator. These tests show that the spectral emissivity of most surface types can be retrieved for dry scenes in the 350–600 cm−1 region, with an absolute uncertainty ranging from 0.005 to 0.01. In addition, the quality of the retrieval is quantified with respect to the precipitable water vapour content of the scene, and the uncertainty caused by the correlation of emissivity with surface temperature is investigated. Based on these investigations, a road map is recommended for the development of the operational emissivity product

    Cirrus cloud identification from airborne far-infrared and mid-infrared spectra

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    Airborne interferometric data, obtained from the Cirrus Coupled Cloud-Radiation Experiment (CIRCCREX) and from the PiknMix-F field campaign, are used to test the ability of a machine learning cloud identification and classification algorithm (CIC). Data comprise a set of spectral radiances measured by the Tropospheric Airborne Fourier Transform Spectrometer (TAFTS) and the Airborne Research Interferometer Evaluation System (ARIES). Co-located measurements of the two sensors allow observations of the upwelling radiance for clear and cloudy conditions across the far-and mid-infrared part of the spectrum. Theoretical sensitivity studies show that the performance of the CIC algorithm improves with cloud altitude. These tests also suggest that, for conditions encompassing those sampled by the flight campaigns, the additional information contained within the far-infrared improves the algorithm's performance compared to using mid-infrared data only. When the CIC is applied to the airborne radiance measurements, the classification performance of the algorithm is very high. However, in this case, the limited temporal and spatial variability in the measured spectra results in a less obvious advantage being apparent when using both mid-and far-infrared radiances compared to using mid-infrared information only. These results suggest that the CIC algorithm will be a useful addition to existing cloud classification tools but that further analyses of nadir radiance observations spanning the infrared and sampling a wider range of atmospheric and cloud conditions are required to fully probe its capabilities. This will be realised with the launch of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission, ESA's 9th Earth Explorer
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